Energy-efficiency impacts of an air-quality feedback device in residential buildings: An agent-based modeling assessment

Jensen, Thorben; Holtz, Georg; Baedeker, Carolin; Chappin, E.J.L.

doi:10.1016/j.enbuild.2015.11.067

Cited by 32 publications

(41 citation statements)

References 32 publications

(23 reference statements)

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“…However, validation was focused on aggregate (macro), rather than individual (micro) behavior. Jensen et al (2016) develop an agent-based model to assess energy-efficiency impacts of an air-quality feedback device in a German city. A household agent makes two decisions: whether to adopt a feedback device and whether to practice a specific energy-saving behavior.…”

Section: Theory Of Planned Behaviormentioning

confidence: 99%

Empirically grounded agent-based models of innovation diffusion: a critical review

2017

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Innovation diffusion has been studied extensively in a variety of disciplines, including sociology, economics, marketing, ecology, and computer science. Traditional literature on innovation diffusion has been dominated by models of aggregate behavior and trends. However, the agent-based modeling (ABM) paradigm is gaining popularity as it captures agent heterogeneity and enables fine-grained modeling of interactions mediated by social and geographic networks. While most ABM work on innovation diffusion is theoretical, empirically grounded models are increasingly important, particularly in guiding policy decisions. We present a critical review of empirically grounded agent-based models of innovation diffusion, developing a categorization of this research based on types of agent models as well as applications. By connecting the modeling methodologies in the fields of information and innovation diffusion, we suggest that the maximum likelihood estimation framework widely used in the former is a promising paradigm for calibration of agent-based models for innovation diffusion. Although many advances have been made to standardize ABM methodology, we identify four major issues in model calibration and validation, and suggest potential solutions.

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Section: Theory Of Planned Behaviormentioning

confidence: 99%

Empirically grounded agent-based models of innovation diffusion: a critical review

2017

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“…The savings from adopting shock ventilation have been shown to amount to an average of approximately 8% (Lovric, 2015;Jensen et al, 2016).…”

Section: The Co 2 Meter Case Studymentioning

confidence: 99%

“…This study therefore aims to use simulation modeling to compare and propose marketing strategies for feedback devices ex-ante. This assessment will adopt and refine a simulation model on the diffusion and effect of a CO 2 meter (Jensen et al, 2016). From this, we aim to identify the management strategies for rolling out feedback devices that show the best impact over a range of future scenarios.…”

Section: Introductionmentioning

confidence: 99%

Reducing domestic heating demand: Managing the impact of behavior-changing feedback devices via marketing

Jensen

Chappin

2017

Journal of Environmental Management

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Feedback devices can be used to inform households about their energy-consumption behavior. This may persuade them to practice energy conservation. The use of feedback devices can also-via word of mouth-spread among households and thereby support the spread of the incentivized behavior, e.g. energy-efficient heating behavior. This study investigates how to manage the impact of these environmental innovations via marketing. Marketing activities can support the diffusion of devices. This study aims to identify the most effective strategies of marketing feedback devices. We did this by adapting an agent-based model to simulate the roll-out of a novel feedback technology and heating behavior within households in a virtual city. The most promising marketing strategies were simulated and their impacts were analyzed. We found it particularly effective to lend out feedback devices to consumers, followed by leveraging the social influence of well-connected individuals, and giving away the first few feedback devices for free. Making households aware of the possibility of purchasing feedback devices was found to be least effective. However, making households aware proved to be most cost-efficient. This study shows that actively managing the roll-out of feedback devices can increase their impacts on energy-conservation both effectively and cost-efficiently.

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“…Complex systems scale from large systems like ecosystem (Levin 1998;Grimm et al 2005) or social ecological systems (Olsson et al 2004) to smaller systems such as secure authentication systems (Habib et al 2011) or buildings Oosterhuis (2012) and their energy system Menassa 2010, 2011;Jensen et al 2016). Limited area notwithstanding, the analysis of a building's energy system is a complex task as it consists of several subsystems.…”

Section: Buildings As Casmentioning

confidence: 99%

“…The agent based modeling can be used to handle such dynamic parameters. For example, the dynamic nature of occupants' behavior can be correlated with the impact on energy consumption in commercial buildings Menassa 2010, 2011) or in managing ventilation system in residential buildings (Jensen et al 2016). There are several bottom up approaches put forward for the agent based modeling.…”

Section: Buildings As Casmentioning

confidence: 99%

Complex building’s energy system operation patterns analysis using bag of words representation with hierarchical clustering

Habib

Hayat

Zucker

2016

Complex Adapt Syst Model

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Purpose Due to the large quantity of data that are recorded in energy efficient buildings, understanding the behavior of various underlying operations has become a complex and challenging task. This paper proposes a method to support analysis of energy systems and validates it using operational data from a cold water chiller. The method automatically detects various operation patterns in the energy system. Methods The use of k-means clustering is being proposed to automatically identify the On (operational) cycles of a system operating with a duty cycle. The latter’s data is subsequently transformed to symbolic representations by using the symbolic aggregate approximation method. Afterward, the symbols are converted to bag of words representation (BoWR) for hierarchical clustering. A gap statistics method is used to find the best number of clusters in the data. Finally, operation patterns of the energy system are grouped together in each cluster. An adsorption chiller, operating under real life conditions, supplies the reference data for validation. Results The proposed method has been compared with dynamic time warping (DTW) method using cophenetic coefficients and it has been shown that the BoWR has produced better results as compared to DTW. The results of BoWR are further investigated and for finding the optimal number of clusters, gap statistics have been used. At the end, interesting patterns of each cluster are discussed in detail. Conclusion The main goal of this research work is to provide analysis algorithms that automatically find the various patterns in the energy system of a building using as little configuration or field knowledge as possible. A bag of word representation method with hierarchical clustering has been proposed to assess the performance of a building energy system.

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Energy-efficiency impacts of an air-quality feedback device in residential buildings: An agent-based modeling assessment

Cited by 32 publications

References 32 publications

Empirically grounded agent-based models of innovation diffusion: a critical review

Empirically grounded agent-based models of innovation diffusion: a critical review

Reducing domestic heating demand: Managing the impact of behavior-changing feedback devices via marketing

Complex building’s energy system operation patterns analysis using bag of words representation with hierarchical clustering

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